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• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• The genomic complexity of sporadic and inherited retinoblastoma with a matched orthotopic xenograft

  Retinoblastoma is a pediatric cancer of the developing retina. All retinoblastomas are believed to initiate with biallelic inactivation of the RB1 gene. To identify subsequent genetic lesions in retinoblastoma, we performed whole genome sequencing of tumor and normal DNA of 4 children with retinoblastoma and one matched orthotopic xenograft. Both alleles of RB1 were inactivated in the tumor samples. 3 of the patients had sporadic retinoblastoma and one patient had inherited retinoblastoma. Overall, there were few single nucleotide changes in coding regions of the genome and some of the tumors had few chromosomal lesions. There were very few new genetic lesions in the xenograft compared to the primary tumor. These data suggest that the genome in retinoblastoma is more stable than previously believed and there are relatively few recurrent genetic lesions in known cancer pathways other than the RB1 pathway.

  Study phs000352

• Genetic landscape of pediatric Retinoblastoma

  Retinoblastoma is a pediatric cancer of the developing retina. All retinoblastomas are believed to initiate with biallelic inactivation of the RB1 gene. To identify subsequent genetic lesions in retinoblastoma, we performed whole genome sequencing of tumor and normal DNA of 4 children with retinoblastoma and one matched orthotopic xenograft. Both alleles of RB1 were inactivated in the tumor samples. 3 of the patients had sporadic retinoblastoma and one patient had inherited retinoblastoma. Overall, there were few single nucleotide changes in coding regions of the genome and some of the tumors had few chromosomal lesions. There were very few new genetic lesions in the xenograft compared to the primary tumor. These data suggest that the genome in retinoblastoma is more stable than previously believed and there are relatively few recurrent genetic lesions in known cancer pathways other than the RB1 pathway.

  Study EGAS00001000346

• Genetic Evaluation of Autoinflammatory Diseases

  Many pediatric patients with early-onset autoinflammatory disease (AID) phenotypes are mutation-negative for genetically known AIDs. Recent data suggest a role for Type-I interferon (IFN) dysregulation in causing AID phenotypes with clinical features that are distinct from those found in patients with IL-1 mediated AIDs. We screened patients for the presence of an IFN-response gene signature (IRS) to characterize their clinical phenotypes, IFN-related biomarkers, and genetic causes.

  Study phs001946

• Matching of actionable mutations with therapies in cancer patients: comparison of three commercial decision support platforms

  Purpose: In oncology, precision medicine centers on tailoring the most appropriate therapy to a patient according to their tumor molecular profile. We addressed the question whether there is a consensus in the classification of actionability of somatic variants and their alignment to treatment recommendations. To this end, we evaluated three commercial clinical decision support tools to assess their variant classification and drug matching strategies.Methods: In this two centers study 48 patients with metastatic breast (n=12), colorectal (n=17) or non-small cell lung cancer (n=19) were recruited based on circulating tumor DNA levels in peripheral blood. In individual patients’ plasma samples, we established somatic copy number alterations and somatic mutations across a 77 cancer-associated gene panel and exposed the obtained molecular profiles to the decision support packages NAVIFY Mutation Profiler (NMP; Roche), Qiagen Clinical Insight (QCI) Interpret (Qiagen) and CureMatch Bionov (CureMatch).Results: In the plasma samples, altogether 492 somatic alterations were assessed. Each decision support platform varied in their format of data input, mode of variant classification and strategies for identifying druggable targets and clinical trials, which resulted in discrepancies in tier classification as well as designations of actionability. The frequency of concordant actionable events for tier I-A or tier I-B classifications, i.e. those with the strongest clinical evidence, was only 4.3%, 9.5% and 28.4% when comparing NMP with QCI, NMP with CureMatch, and CureMatch with QCI, respectively. As a consequence, the obtained treatment recommendations differed drastically, and alignment of treatment recommendations was limited to established predictive markers.Conclusions: The lack of standards for the extraction of treatment recommendations from comprehensive tumor molecular profiling data challenge the promising concepts of precision oncology.

  Study EGAS00001004383

• Relationship between low LDL cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: a US-based cross-sectional observational study using electronic medical records

  Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.

  Study phs001588

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Integrated Molecular Profilting in Advanced Cancers Trial

  The present protocol seeks to provide molecular profiling data to the treating physician for patients with advanced breast, non-small cell lung, colorectal, genitourinary, pancreatobiliary gastrointestinal, upper aerodigestive tract, gynecological, melanoma, unknown primary, and rare carcinomas, as well as patients who are phase I trial candidates, in order to help identify which standard regimens or clinical trials of molecularly targeted therapies may be most appropriate for the individual patient.

  Study EGAS00001001897

• Meningioma Exome

  Meningioma Exome

  Dataset EGAD00001000099